Top Machine Learning Jobs in Calgary

As a Machine Learning Engineer, develop ML models, data pipelines, conduct analytics, and work on image and video inference for fish health and behavior.

Lead technical initiatives in ML product development focusing on LLM and NLP systems. Mentor engineers, design models, and oversee data strategies while ensuring operational excellence and model performance.

The Senior Machine Learning Ops Engineer will design and build machine learning operations infrastructure, manage ML pipelines, experiment tracking, model deployment, and collaborate with engineering teams to enhance data and ML processes.

The Senior AI Engineer will develop AI features for observability tools, collaborate with cross-functional teams, and deliver scalable AI solutions.

The AI/ML Engineer will design and deploy advanced AI models, optimize performance, and directly engage with government officials to transform industries through innovative AI solutions.

As an Associate Technical Architect in Machine Learning, you will design and develop advanced ML models on AWS, ensuring scalability and reliability while collaborating with cross-functional teams.

As a Senior Fullstack Software Engineer, you'll operationalize ML models, collaborate with data scientists, maintain CI/CD pipelines, and improve ML infrastructure and frontend integrations.

The role involves building and maintaining an MLOps platform, optimizing machine learning models for security data, and collaborating with teams to enhance data processing systems.

Lead the development of scalable machine learning pipelines and client engagements. Design MLOps processes, implement CI/CD, and convert prototypes into production solutions.

Lead an AI/ML/Data Science team to develop and deploy machine learning solutions for robotics, focusing on innovative capabilities and cost-effective cloud processing pipelines.

Design, build, and deploy scalable ML solutions using GCP and Vertex AI. Collaborate with teams to operationalize models and monitor performance.

As a Senior Machine Learning Engineer, you will build and optimize ML models, design ML infrastructure, and collaborate with teams to enhance AI products for cybersecurity.

The Machine Learning Engineer II will develop and maintain AI/ML systems, manage cloud operations, and collaborate across teams to deploy ML-powered tools.

The Senior ML Performance Engineer will architect a Performance Testing Platform, optimize ML performance on GPUs, and validate model efficiency.

The Senior AI/ML Engineer will architect, build, and deploy AI systems, working with clients to understand their needs and applying MLOps practices to enhance AI services.

Develop scalable machine learning models, collaborate with teams, create proofs of concepts, and write maintainable code while engaging in the entire ML development cycle.

The AI/ML Engineer will design and develop AI-powered applications, automate workflows, and integrate AI into BPM's daily operations, ensuring they deliver business value.

The Machine Learning Engineer will develop and deploy ML models, leveraging analytical skills to automate processes and reveal data value.

Lead and grow a global engineering team, drive technical strategy, and ensure alignment between client goals and engineering solutions in a remote setting.

The role involves developing ML systems for enterprise workflows, focusing on user understanding, task prediction, and optimizing ML pipelines. Key responsibilities include designing scalable evaluation frameworks and collaborating with teams to deliver production-ready solutions.

As a Software & ML Intern, you will build data pipelines and cloud-based tools, collaborating extensively to develop scalable scientific software solutions.

As a Machine Learning Engineer/Scientist, you will develop ML systems for cryopreservation research, manage data pipelines, and deploy models for scientific insight.

The Senior Machine Learning Engineer will design advanced ML solutions, work on LLMs, and collaborate with cross-functional teams to drive innovation in healthcare and life sciences.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.

Contribute to developing machine learning models for multi-scale biology, focusing on design, deployment and optimization across teams and technologies.